The teachings presented herein relate generally to calibration of output display devices. The teachings presented herein relate more specifically to calibration of color displays.
The need for “soft-proofing” continues to grow especially in the graphic arts and production color markets. It is also expected to play an increasingly important role in distributed and remote color management applications. To be useful, soft-proofing depends for its deployment upon having a calibrated display. At the high end of the graphic arts market, users are willing to calibrate their displays using expensive instruments. Further down market, users may use interactive visual calibration techniques. These visual techniques are not as accurate as their measurement-based counterparts; but they are relatively inexpensive, and the quality is sufficient for many applications.
An important color characteristic of display devices is the 1-dimensional tone response of each of the R, G and B (red, blue, and green) primaries. For CRTs (Cathode-Ray Tubes) and many LCDs (Liquid Crystal Displays), this tone response is described by a power-law relationship between input digital value and displayed luminance. The exponent of the power-law is frequently referred to as “gamma”. The focus of the teachings provided herein below is on the estimation of correct gamma for a given display as user determined by the employment of visual tasks.
Previous techniques for gamma estimation either a) assume all three channels are identical; or b) provide the same controls for all three channels. Perhaps the most well-known prior art approach involves adjusting the digital value of a continuous-tone patch (which could be pure R, G, B or R=G=B) until its lightness matches that of a halftone pattern generated using alternating on/off lines. One GUI (Graphical User Interface) implementation providing a user visual task for luminance-matching is as shown in FIG. 1. Here Gamma determination is made by 50% luminance-matching. The sliders 100 associated with each color patch R, G, and B, are user adjusted until the left half 110 and right half 120 are determined as matching in lightness. In this particular embodiment, the left half 110 has exactly ½ black and ½ full on continuous-tone color as provided here by interlaced horizontal stripes alternating between black and contone (continuous-tone) color.
The assumption relied upon here is that the fractional luminance of the halftone pattern is 50% (as provided in the left half 110), i.e. it is halfway between the luminance provided at full-off and full-on. The desired determined value of gamma is estimated from the digital value needed to match the 50% fractional luminance by the equation 1 which follows:YHT=(Dselect−Doffset)γγ=log(YHT)/log(Dselect−Doffset)  Eqn. (1)where Dselect is the digital value selected in the visual task, YHT is the fractional luminance of the 50% halftone pattern. Doffset is the offset value below which there is no discernable response from the device. This parameter is obtained separately either from measurements or from visual tasks.
The technique just described is in widespread use within many commercially available display calibration tools, and it is believed was first mentioned in the publication to William B. Cowan, “An Inexpensive Scheme For Calibration Of A Colour Monitor In Terms Of CIE Standard Coordinates”, Computer Graphics, Vol. 17, No. 3, pp. 315-321.
Visual tasks that assume the same gamma for the 3 channels use greyscale (R=G=B) images or patches, and are generally simple to execute. However, the equi-gamma assumption is often incorrect. The Photoshop™ 3.0 calibration tool for example attempts to correct for this assumption by having the users perform a grey-balance adjustment jointly with the 50% greyscale luminance matching task. However, this is an iterative procedure that can produce inconsistent results from observer to observer.
Since the power-law response is a channel-wise phenomenon, it makes more sense to estimate gamma separately for each of the 3 channels as described above and shown by FIG. 1. The problem with this approach is that luminance judgments are very difficult to perform for the blue primary. Vision scientists believe that the blue (short-wavelength) sensor response does not contribute to the human visual system's luminance channel. The medium and long wavelength sensors also respond, but to a much lesser extent, to light generated by the blue phosphor of a CRT or other color display device. Hence, relatively large changes to the strength of the blue signal yield small changes in the visual response. The resulting difficulties in the visual task produce large variances in the estimated gamma value for blue.
What is needed is a straight-forward visual method of determining the gamma for the blue primary that is easier to perform and more consistent than the luminance-matching task solution provided by the prior art.
Disclosed in embodiments herein is a method of determining correct color gamma for a display device as driven by three primary signals. The method comprises luminance-matching to determine the respective gamma value for two of the three primary signals and, grey-balancing to determine the respective gamma value for the remaining primary signal of the three primary signals.
Further disclosed in embodiments herein is a method of determining calibration functions for a display device. The method comprises luminance-matching to determine the respective calibration functions for at least two primary signals and, grey-balancing to determine the respective calibration function for at least one additional primary signal, where the grey-balancing employs the respective calibration functions for the at least two primary signals as determined in the luminance-matching step.
Further disclosed in embodiments herein is a visually based method for determining gamma color correction for a display device. This method comprises providing a luminance-matching visual task on the display device and capturing the user selection of a first color indicated by the user as a match in luminance. The gamma for the first color is then calculated using the captured user selection indicated as a match in luminance. Then a grey-balancing visual task for a second color is provided on the display device, which employs the calculated gamma for the first color in the display of the grey-balancing visual task. This is followed by capturing the user selection of the second color indicated by the user as a match in chromaticity, and calculating the gamma for the second color using the user selection indicated as a match in chromaticity.